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Automates pre-development workflow for large-scale complex tasks. Use when the user mentions "rewrite", "migrate", "overhaul", "refactor entire project", "transform", "rebuild in [language]", "spec-driven", or describes any large-scale project transformation that requires planning before coding. Also triggers on Chinese keywords: "改造", "重写", "迁移", "重构", "大规模", "规范驱动". Performs full project analysis, task decomposition, documentation generation, project-level instruction and native memory surface resolution, progress tracking setup, and then executes the plan within the same session.

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Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

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Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

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This skill should be used when the user asks to "agentize a website", "transform a website", "create an agentfront", "build a WWA app", "make an agent-first website", "turn a website into an agent experience", "agentizer", "wwa transform", or mentions "agentfront" in context of building one from a URL.

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Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.

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Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.

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Load this first for any task involving images, pictures, photos, scans, frames, volumes, or visual data — including reading, writing, filtering, enhancing, denoising, sharpening, deblurring, thresholding, segmenting, masking, detecting, finding or counting objects, removing backgrounds, measuring, comparing, registering, stitching, aligning, cropping, resizing, transforming, or analyzing. Use for image I/O (TIFF, PNG, JPEG, RAW, HDR), histograms, edge detection, color processing, morphology, geometric transforms, deep learning for images, quality assessment, and 3-D volume processing. Also triggers when users describe image problems (dark, noisy, blurry, low contrast, uneven lighting, hazy, color cast) or data exploration tasks (folder of images, characterize data, understand format). Handles microscopy (cells, particles) and general scientific imaging. Routes to sibling skills for medical imaging (DICOM, NIfTI), hyperspectral data, and visual inspection.

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Perform aerospace unit conversions, time conversions, coordinate frame transformations, and rotation representations using Aerospace Toolbox. Use when converting units (length, velocity, angle, acceleration, angular velocity, force, mass, pressure, temperature, density), computing Julian dates or decimal years, transforming between coordinate frames (ECEF, ECI, LLA, flat Earth, geodetic/geocentric, NED, body, wind, stability), or working with rotation representations (Euler angles, DCM, quaternion, Rodrigues vector). Also use when the user asks about aerospace coordinate systems, reference frames, or rotation conventions.

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Analytics engineering across data modeling, dbt, transformation, and semantic layers. Use when building dbt models, designing star schemas, writing staging or mart SQL, configuring data tests, or optimizing warehouse queries.

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Transforme un modèle juridique (.docx ou .odt : contrat, conclusions, assignation, courrier type, procès-verbal…) en formulaire HTML autonome, exécuté hors ligne, qui produit sans IA le document complété, fidèle au modèle, dans son format d'origine : parties optionnelles et alternatives, listes répétées, accords, montants et dates en lettres, calculs, numérotation et renvois. Déclencher dès que l'utilisateur veut « transformer ce modèle en formulaire », « automatiser un modèle », un « modèle à remplir » ou un « générateur d'actes », réutiliser régulièrement un contrat ou une trame, ou demande « fais-moi un modèle de … à remplir » ; aussi pour faire évoluer un formulaire tabellion existant. Pas pour compléter une seule fois un document. Compétence créée par Christophe Quézel-Ambrunaz, Université Savoie Mont Blanc (V.1.1).

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Answer Bevy 0.20 line-of-sight, radius, and cursor picks with Transform distance and facing. Use when a design needs a probe and collider casts belong on the physics skills. Keywords: Bevy, spatial query, viewport_to_world_2d, GlobalTransform, facing, radius.

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We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi

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Use when the user wants to apply a named Higgsfield motion preset, asks about VFX presets, transformation effects, elemental effects, or transition presets. Contains the full named preset library with descriptions and prompt usage.

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Plan and execute a brand transformation — from diagnosis to new brand definition to rollout. Use when the user says "rebrand", "rebranding", "brand refresh", "update the brand", "modernize the brand", "our brand is outdated", "we've outgrown our brand", "the brand needs to change", "brand transformation", "pivot the brand", "we're changing the brand", "the old brand doesn't fit anymore", or when a brand has evolved in direction, audience, or market position and needs its identity to catch up.

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使用 GLM 库实现 Vector3TransformNormal 和 Vector3TransformCoord 函数，模拟 DirectXMath 的行为，并使用 const T& 模板参数以支持多种向量类型。

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Run Hugging Face models in JavaScript or TypeScript with Transformers.js, WebGPU, or WASM across browser, Node.js, Bun, and Deno. Use for client-side or JS-runtime inference, not Python training.

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Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.

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Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).

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Transform, clean, reshape, and preprocess data using pandas and numpy. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

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Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

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HuggingFace Transformers with biomedical LMs (BioBERT, PubMedBERT, BioGPT, BioMedLM) for scientific NLP: NER (genes, diseases, chemicals), relation extraction, QA, text classification, abstract summarization. Covers loading, biomedical tokenization, inference pipelines, fine-tuning. Alternatives: spaCy en_core_sci_lg (rule-based NER), Stanza (biomedical models), NLTK.

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Provides patterns for unit testing mappers, converters, and bean mappings. Validates entity-to-DTO and model transformation logic in isolation. Generates executable mapping tests with MapStruct and custom converter test coverage. Use when writing mapping tests, converter tests, entity mapping tests, or ensuring correct data transformation between DTOs and domain objects.

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Generate test cases using metamorphic testing by applying transformations based on metamorphic properties. Use when you need to expand test suites, test programs without oracles, validate mathematical or algorithmic properties, or detect subtle bugs through input-output relationships. The skill takes a program, original test cases, and metamorphic properties as input, generates new test cases by applying transformations, executes tests, verifies outputs satisfy properties, reports violations and anomalies, and outputs an expanded test suite with property coverage summary. Supports multiple programming languages and property types.

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dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

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